Jia-Bin Huang

"Citations don't matter", says the one with gazillions of citations.

"We believe in slow science", say the groups who publish one paper every week.

Like it or not, the system evaluates researchers with citations. 

Here are practical steps for junior folks 🧵

Three key ideas: 

1⃣ Make your work accessible

2⃣ Make your work memorable

3⃣ Make your work usable

Let's break them down.

*How do you make your work more accessible?*

👉 Disseminate your work through dynamic, engaging media rather than relying solely on a static, boring PDF.

But HOW? 

Make a website, write a social media thread, write a blog post, create a video explainer.

*How to make your work memorable?*

There are several actionable steps. 

The simplest one? Come up with a good name!

Needless to say, the paper title is incredibly important! 

Spend time designing a distinct, memorable title. 

Source: Good Citizen of Computer Vision ()

People memorize your work better when you can tell a clear story that 

*puts your work in the context of existing research*.

Distill your core idea into one concise figure.

Examples:

*How to make your work usable?*

Your work is cited because it empowers others to do their work. 

Don't simply dump your messy codebase online. 
Put effort into polishing and organizing it so people can easily build upon your work.

To further increase your research impact, check out this post that I found particularly insightful:

"Build what you need and use what you build." - @Michael_J_Black

Share the many facets of your work.

To finish up your work, you typically need to 
- write up evaluation script
- implement custom kernel
- reproduce baselines
- process messy data, clean up annotations
- visualize results

All these have values. Share generously to help others.

Of course, aiming to maximize citation counts is the WRONG goal. 

Focus instead on producing research that has real impact. Over time, your work will naturally be appreciated and recognized.

Make them accessible, memorable, and useful!

How to come up with research ideas?

Excited about starting doing research but have no clue?🤷‍♂️🤷🏻‍♀️ Here are some simple methods that I found useful in identifying initial directions.

Check out the thread below 👇

*Find a different dimension*

Just learn a cool idea from others? Think about how you could extend it to another dimension. 

Ex: Text / audio / image / video / graph 

*Relax assumptions*

Identify the underlying assumptions of existing work and try relaxing them to make it work in more unconstrained settings. 

*Make more assumptions*

Take a general approach and tailor it to your SPECIFIC problem. You can then leverage all the domain knowledge (i.e., make more assumptions) to improve the method. 

*Combine two ideas/problems*
 
"To steal ideas from one person is plagiarism. To steal from many is research." - Wilson Mizner 

*Grab a powerful hammer and find all the nails*

Pay attention to new emerging tools in the community.  Apply and adapt them on your problem. 

*Add an adjective*

Given an existing idea X, add an adjective to make it 
- slow➡️ fast
- batch➡️online
- sensitive➡️robust
- centralized➡️distributed
- single-step➡️progressive
- single-level➡️hierarchical
- fixed➡️adaptive, sth-aware
- data-hungry➡️data-efficient
and so on 

*Stress test the state-of-the-art*

Don't simply run on the fixed, boring benchmark datasets. Try it out on diverse, unconstrained examples and see how it fails. It's a great way to identify limitations of existing work. This is where your work can fill the gap. 

That's all! I would love to hear about your approaches for coming up with new ideas.